Dataset Information

Identification of the New Metabolite of Nebivolol Using Liquid Chromatography Coupled with High-Resolution Mass Spectrometry and Chemometrics.

ABSTRACT: In this study, the phase I hepatic metabolism pathway of a cardiovascular drug nebivolol was proposed on the basis of a human liver microsomes assay with the use of LC-HR-MS coupled with the chemometric method. Six biotransformation products were found with the assistance of chemometric analysis. Five of them were identified as the previously reported products of alicyclic hydroxylation and dihydroxylation, aromatic hydroxylation, as well as alicyclic oxidation of the parent compound. Moreover, one metabolite, not reported so far, was found to be a product of N-dealkylation of nebivolol-2-amino-1-(6-fluoro-3,4-dihydro-2H-1-benzopyran-2-yl)ethan-1-ol. The novel metabolite was submitted to an in silico toxicity analysis to assess its biological properties. The applied computational methods indicated a significantly elevated risk of its mutagenic activity, compared to the parent molecule. Several metabolites of the nebivolol described in the literature were not detected in this study, indicating their non-hepatic origin.

SUBMITTER: Trawinski J

PROVIDER: S-EPMC8839339 | biostudies-literature | 2022 Jan

REPOSITORIES: biostudies-literature

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Identification of the New Metabolite of Nebivolol Using Liquid Chromatography Coupled with High-Resolution Mass Spectrometry and Chemometrics.

Trawiński Jakub J Wroński Michał M Gawlik Maciej M Skibiński Robert R

Molecules (Basel, Switzerland) 20220124 3

In this study, the phase I hepatic metabolism pathway of a cardiovascular drug nebivolol was proposed on the basis of a human liver microsomes assay with the use of LC-HR-MS coupled with the chemometric method. Six biotransformation products were found with the assistance of chemometric analysis. Five of them were identified as the previously reported products of alicyclic hydroxylation and dihydroxylation, aromatic hydroxylation, as well as alicyclic oxidation of the parent compound. Moreover, ...[more]

PMID: 35164027

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Project description:Pharmaceuticals released into the aquatic and soil environments can be absorbed by plants and soil organisms, potentially leading to the formation of unknown metabolites that may negatively affect these organisms or contaminate the food chain. The aim of this study was to identify pharmaceutical metabolites through a triplet approach for metabolite structure prediction (software-based predictions, literature review, and known common metabolic pathways), followed by generating in silico mass spectral libraries and applying various mass spectrometry modes for untargeted LC-qTOF analysis. Therefore, Eisenia fetida and Lactuca sativa were exposed to a pharmaceutical mixture (atenolol, enrofloxacin, erythromycin, ketoprofen, sulfametoxazole, tetracycline) under hydroponic and soil conditions at environmentally relevant concentrations. Samples collected at different time points were extracted using QuEChERS and analyzed with LC-qTOF in data-dependent (DDA) and data-independent (DIA) acquisition modes, applying both positive and negative electrospray ionization. The triplet approach for metabolite structure prediction yielded a total of 3762 pharmaceutical metabolites, and an in silico mass spectral library was created based on these predicted metabolites. This approach resulted in the identification of 26 statistically significant metabolites (p < 0.05), with DDA + and DDA - outperforming DIA modes by successfully detecting 56/67 sample type:metabolite combinations. Lettuce roots had the highest metabolite count (26), followed by leaves (6) and earthworms (2). Despite the lower metabolite count, earthworms showed the highest peak intensities, closely followed by roots, with leaves displaying the lowest intensities. Common metabolic reactions observed included hydroxylation, decarboxylation, acetylation, and glucosidation, with ketoprofen-related metabolites being the most prevalent, totaling 12 distinct metabolites. In conclusion, we developed a high-throughput workflow combining open-source software with LC-HRMS for identifying unknown metabolites across various sample types.

Dataset Information

Identification of the New Metabolite of Nebivolol Using Liquid Chromatography Coupled with High-Resolution Mass Spectrometry and Chemometrics.

Publications

Identification of the New Metabolite of Nebivolol Using Liquid Chromatography Coupled with High-Resolution Mass Spectrometry and Chemometrics.

Similar Datasets

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